Columbia University

∙ New York , United States ∙ 0 followers

Located In New York City, The School at Columbia University is a Private K-8 Day School serving neighborhood families and Columbia University employees.

Featured Researchers

Wei Liu
224 publications
Lei Zhang
207 publications
Wei Zhang
182 publications
Xi Chen
147 publications
Li Wang
77 publications
David M. Blei
76 publications
Shih-Fu Chang
69 publications
Fan Zhang
66 publications
Cynthia Rudin
63 publications
Yang Feng
60 publications
Dong Liu
52 publications

How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?

In recent years there has been an increasing trend in which data scienti...
09/08/2019 ∙ by Yaoli Mao, et al. ∙ 71 ∙ share

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AutoML using Metadata Language Embeddings

As a human choosing a supervised learning algorithm, it is natural to be...
10/08/2019 ∙ by Iddo Drori, et al. ∙ 36 ∙ share

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Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax

The Gumbel-Softmax is a continuous distribution over the simplex that is...
12/19/2019 ∙ by Andres Potapczynski, et al. ∙ 36 ∙ share

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One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples

Modern image classification systems are often built on deep neural netwo...
11/25/2019 ∙ by Chang Xiao, et al. ∙ 33 ∙ share

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FaceShapeGene: A Disentangled Shape Representation for Flexible Face Image Editing

Existing methods for face image manipulation generally focus on editing ...
05/06/2019 ∙ by Sen-Zhe Xu, et al. ∙ 28 ∙ share

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Theme-Matters: Fashion Compatibility Learning via Theme Attention

Fashion compatibility learning is important to many fashion markets such...
12/12/2019 ∙ by Jui-Hsin Lai, et al. ∙ 28 ∙ share

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SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design

Parametric computer-aided design (CAD) is the dominant paradigm in mecha...
07/16/2020 ∙ by Ari Seff, et al. ∙ 26 ∙ share

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Noise2Blur: Online Noise Extraction and Denoising

We propose a new framework called Noise2Blur (N2B) for training robust i...
12/03/2019 ∙ by Huangxing Lin, et al. ∙ 25 ∙ share

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Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling

We consider the problem of inferring the values of an arbitrary set of v...
02/06/2019 ∙ by Hao Wang, et al. ∙ 24 ∙ share

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Unrestricted Adversarial Attacks for Semantic Segmentation

Semantic segmentation is one of the most impactful applications of machi...
10/06/2019 ∙ by Guangyu Shen, et al. ∙ 23 ∙ share

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Stacked Semantic-Guided Network for Zero-Shot Sketch-Based Image Retrieval

Zero-shot sketch-based image retrieval (ZS-SBIR) is a task of cross-doma...
04/03/2019 ∙ by Hao Wang, et al. ∙ 22 ∙ share

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Learning Your Way Without Map or Compass: Panoramic Target Driven Visual Navigation

We present a robot navigation system that uses an imitation learning fra...
09/20/2019 ∙ by David Watkins-Valls, et al. ∙ 21 ∙ share

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Learning to Compose Dynamic Tree Structures for Visual Contexts

We propose to compose dynamic tree structures that place the objects in ...
12/05/2018 ∙ by Kaihua Tang, et al. ∙ 20 ∙ share

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Weakly Supervised Attention Networks for Fine-Grained Opinion Mining and Public Health

In many review classification applications, a fine-grained analysis of t...
09/30/2019 ∙ by Giannis Karamanolakis, et al. ∙ 20 ∙ share

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Zero Shot Learning on Simulated Robots

In this work we present a method for leveraging data from one source to ...
10/04/2019 ∙ by Robert Kwiatkowski, et al. ∙ 18 ∙ share

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Controversial stimuli: pitting neural networks against each other as models of human recognition

Distinct scientific theories can make similar predictions. To adjudicate...
11/21/2019 ∙ by Tal Golan, et al. ∙ 18 ∙ share

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COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation

To combat COVID-19, both clinicians and scientists need to digest the va...
07/01/2020 ∙ by Qingyun Wang, et al. ∙ 18 ∙ share

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Towards Understanding Fast Adversarial Training

Current neural-network-based classifiers are susceptible to adversarial ...
06/04/2020 ∙ by Bai Li, et al. ∙ 17 ∙ share

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Practical Deep Reinforcement Learning Approach for Stock Trading

Stock trading strategy plays a crucial role in investment companies. How...
11/19/2018 ∙ by Zhuoran Xiong, et al. ∙ 16 ∙ share

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TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation

Deep generative models have been successfully applied to many applicatio...
01/28/2019 ∙ by Zihan Ding, et al. ∙ 16 ∙ share

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Unsupervised Deep Tracking

We propose an unsupervised visual tracking method in this paper. Differe...
04/03/2019 ∙ by Ning Wang, et al. ∙ 16 ∙ share

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ES-MAML: Simple Hessian-Free Meta Learning

We introduce ES-MAML, a new framework for solving the model agnostic met...
09/25/2019 ∙ by Xingyou Song, et al. ∙ 16 ∙ share

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Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features

The ability to extrapolate gene expression dynamics in living single cel...
01/15/2020 ∙ by Nanyan Zhu, et al. ∙ 14 ∙ share

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AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks

Generative Adversarial Networks (GANs) are formulated as minimax game pr...
06/16/2020 ∙ by Yuesong Tian, et al. ∙ 13 ∙ share

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Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces

We present a new algorithm ASEBO for conducting optimization of high-dim...
03/07/2019 ∙ by Krzysztof Choromanski, et al. ∙ 12 ∙ share

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PointHop: An Explainable Machine Learning Method for Point Cloud Classification

An explainable machine learning method for point cloud classification, c...
07/30/2019 ∙ by Min Zhang, et al. ∙ 12 ∙ share

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Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics

We present an end-to-end statistical framework for personalized, accurat...
08/27/2019 ∙ by Iñigo Urteaga, et al. ∙ 12 ∙ share

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Rethinking Generative Coverage: A Pointwise Guaranteed Approach

All generative models have to combat missing modes. The conventional wis...
02/13/2019 ∙ by Peilin Zhong, et al. ∙ 12 ∙ share

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Individual predictions matter: Assessing the effect of data ordering in training fine-tuned CNNs for medical imaging

We reproduced the results of CheXNet with fixed hyperparameters and 50 d...
12/08/2019 ∙ by John R. Zech, et al. ∙ 12 ∙ share

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AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

Can one build a knowledge graph (KG) for all products in the world? Know...
06/24/2020 ∙ by Xin Luna Dong, et al. ∙ 12 ∙ share

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General Partial Label Learning via Dual Bipartite Graph Autoencoder

We formulate a practical yet challenging problem: General Partial Label ...
01/05/2020 ∙ by Brian Chen, et al. ∙ 11 ∙ share

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Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition

In this paper, we aim to address the problem of human interaction recogn...
11/01/2018 ∙ by Xiangbo Shu, et al. ∙ 10 ∙ share

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Moment Matching for Multi-Source Domain Adaptation

Conventional unsupervised domain adaptation (UDA) assumes that training ...
12/04/2018 ∙ by Xingchao Peng, et al. ∙ 10 ∙ share

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Fully-Featured Attribute Transfer

Image attribute transfer aims to change an input image to a target one w...
02/17/2019 ∙ by De Xie, et al. ∙ 10 ∙ share

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Substituting Gadolinium in Brain MRI Using DeepContrast

Cerebral blood volume (CBV) is a hemodynamic correlate of oxygen metabol...
01/15/2020 ∙ by Haoran Sun, et al. ∙ 9 ∙ share

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Real-time Universal Style Transfer on High-resolution Images via Zero-channel Pruning

Extracting effective deep features to represent content and style inform...
06/16/2020 ∙ by Jie An, et al. ∙ 9 ∙ share

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Smoothed Analysis of Online and Differentially Private Learning

Practical and pervasive needs for robustness and privacy in algorithms h...
06/17/2020 ∙ by Nika Haghtalab, et al. ∙ 9 ∙ share

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Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling

Many real-world systems studied are governed by complex, nonlinear dynam...
11/29/2018 ∙ by Josue Nassar, et al. ∙ 8 ∙ share

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Deep Reinforcement Learning for Intelligent Transportation Systems

Intelligent Transportation Systems (ITSs) are envisioned to play a criti...
12/03/2018 ∙ by Xiao-Yang Liu, et al. ∙ 8 ∙ share

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Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes

We propose a new class of structured methods for Monte Carlo (MC) sampli...
05/29/2019 ∙ by Krzysztof Choromanski, et al. ∙ 8 ∙ share

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Bayesian Tensor Filtering: Smooth, Locally-Adaptive Factorization of Functional Matrices

We consider the problem of functional matrix factorization, finding low-...
06/10/2019 ∙ by Wesley Tansey, et al. ∙ 8 ∙ share

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SemEval-2015 Task 10: Sentiment Analysis in Twitter

In this paper, we describe the 2015 iteration of the SemEval shared task...
12/05/2019 ∙ by Sara Rosenthal, et al. ∙ 8 ∙ share

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Valid Causal Inference with (Some) Invalid Instruments

Instrumental variable methods provide a powerful approach to estimating ...
06/19/2020 ∙ by Jason Hartford, et al. ∙ 8 ∙ share

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Image Outpainting and Harmonization using Generative Adversarial Networks

Although the inherently ambiguous task of predicting what resides beyond...
12/23/2019 ∙ by Basile Van Hoorick, et al. ∙ 7 ∙ share

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(Sequential) Importance Sampling Bandits

The multi-armed bandit (MAB) problem is a sequential allocation task whe...
08/08/2018 ∙ by Iñigo Urteaga, et al. ∙ 6 ∙ share

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Multi-level Multimodal Common Semantic Space for Image-Phrase Grounding

We address the problem of phrase grounding by learning a multi-level com...
11/28/2018 ∙ by Hassan Akbari, et al. ∙ 6 ∙ share

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Hierarchical Macro Strategy Model for MOBA Game AI

The next challenge of game AI lies in Real Time Strategy (RTS) games. RT...
12/19/2018 ∙ by Qiang Fu, et al. ∙ 6 ∙ share

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Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes

Recent advances in on-policy reinforcement learning (RL) methods enabled...
03/08/2019 ∙ by Bohan Wu, et al. ∙ 6 ∙ share

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Two models of double descent for weak features

The "double descent" risk curve was recently proposed to qualitatively d...
03/18/2019 ∙ by Mikhail Belkin, et al. ∙ 6 ∙ share

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How many variables should be entered in a principal component regression equation?

We study least squares linear regression over N uncorrelated Gaussian fe...
06/04/2019 ∙ by Ji Xu, et al. ∙ 6 ∙ share

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